def storeWindowMatches():
myDh = read_JSON.DataHandler()
libraries = {'harris': np.load('./library_match_1_segment_harris.npy'),
'histogram': np.load('./library_match_1_segment_histogram.npy')}
windowMatches = {}
ds = myDh.eventWindowArrayPerActor
total = 0
for actor in ds:
for data in ds[actor]:
total+=1
iter = 0
for actor in ds:
windowMatches[actor] = {}
for data in ds[actor]:
found, frames, scores = findWindow(libraries, data, actor)
win_id = data['window']
windowMatches[actor][f'w_{win_id}'] = {
'matched': found,
'frames': list(map(int, frames)),
'scores': list(map(float, scores))
}
for e in range(0, len(frames)):
windowMatches[actor][f'w_{win_id}'][f'e_{e+1}'] = {}
windowMatches[actor][f'w_{win_id}'][f'e_{e+1}']['frame'] = int(frames[e])
windowMatches[actor][f'w_{win_id}'][f'e_{e+1}']['score'] = float(scores[e])
iter += 1
print(f'progress {iter/total:.2f}')
with open('stored_json\\player_window_event_matches.txt', 'w') as outfile:
json.dump(windowMatches, outfile)
def findEventsInLibrary():
dH = read_JSON.DataHandler()
libraries = {}
print('Loading libraries...')
for ft_name in u.feature_config:
print(ft_name)
libraries[ft_name] = np.load(u.feature_config[ft_name]['library'])
print(libraries[ft_name].shape)
print(' loaded _<')
for actor in dH.eventWindowArrayPerActor:
window_event_features = ['dummy']
win_indx = 1
while len(window_event_features) > 0:
window_event_features = glob.glob(
f'./resources/event_queries/{actor}_w{win_indx}_e*_harris.npy')
if len(window_event_features) == 0:
break
matched, scores, frames = findWindowInLibrary(
libraries, window_event_features)
print(
f'file: {window_event_features} match: {matched} scores: {scores} '
)
for frame in frames:
print(f'frame: {frameOffsetToCommentatorFrame(1,frame)}')
video_handler.read_frame(
com_path, u.frameOffsetToCommentatorFrame(1, frame),
f'{window_event_features[0]} events: {len(window_event_features)}'
)
win_indx += 1
def __init__(self):
self.com_path = 'C:\save\\2018-03-02_P11.mp4'
self.dH = read_JSON.DataHandler()
self.guiDs = {}
self.libraries = {
'harris': np.load('./library_match_1_segment_harris.npy'),
'histogram': np.load('./library_match_1_segment_histogram.npy')
}
def createEventFeatures():
eventData = {}
dH = read_JSON.DataHandler()
ds = dH.eventWindowArrayPerActor
roi = [0.25, 0.55, 0.35, 0.65]
for actor in ds:
eventData[actor] = {}
vid_path = u.playerToPath(actor)
window_count = 0
for window in ds[actor]:
window_count += 1
eventData[actor][f'w_{window_count}'] = {}
event_count = 0
for event_time in window['event_times']:
event_count += 1
event_frame = u.event_time_to_stream_frame(
event_time, u.player_id[actor], 1)
frame = video_handler.get_frame(vid_path, event_frame)
frame_roi = ft.get_ROI(frame, roi)
harris_result = ft.get_harris_feature(frame_roi)
hist_result = ft.extract_frame_histogram(frame_roi)
# canny_result = ft.get_canny_feature(frame_roi)
harris_filename = f'./resources/event_queries/{actor}_w{window_count}_e{event_count}_harris'
hist_filename = f'./resources/event_queries/{actor}_w{window_count}_e{event_count}_histogram'
eventData[actor][f'w_{window_count}'][f'e_{event_count}'] = {
'event_frame': event_frame,
'harris_filename': harris_filename,
'hist_filename': hist_filename
}
np.save(harris_filename, harris_result)
np.save(hist_filename, hist_result)
# np.save(f'./resources/event_queries/{actor}_w{window_count}_e{event_count}_canny', canny_result)
#dump event data json
with open('stored_json\\player_event_features.txt', 'w') as outfile:
json.dump(eventData, outfile)
def getRankedList():
myDh = read_JSON.DataHandler()
ds = myDh.eventWindowArrayPerActor
stats = {}
for actor in ds:
for data in ds[actor]:
window_num = data['window']
stored_window_match = u.getWindowStoredData(actor, window_num)
if stored_window_match != None:
if stored_window_match['matched'] == False:
window_stats = {}
window_stats['weight'] = data['total_weight']
window_stats['data'] = data
window_stats['actor'] = actor
stats[f'{actor}_{window_num}'] = window_stats
sorted_keys = sorted(stats, key=lambda x: (-1*stats[x]['weight']))
result_dict_list = []
for key in sorted_keys:
temp_dict = stats[key]
temp_dict['window_name'] = key
result_dict_list.append(temp_dict)
print(result_dict_list)
return result_dict_list
def displayEventsDatasetDemo(display_events=10, show_frames_before=120):
myDh = read_JSON.DataHandler()
ds = myDh.dataset
display_event_count = 0
for event in ds:
event_time = event['date']
event_playerid = player_id[event['actor']]
event_filename = f"2018-03-02_P{event_playerid}"
event_framenumber = utils.event_time_to_stream_frame(
event_time, event_playerid, 1)
video_path = f'C:\save\\{event_filename}.mp4'
vid = read_video(video_path)
event_type = event['event_type']
event_actor = event['actor']
display_video(vid,
event_framenumber - show_frames_before,
title=f'{event_type} {event_actor}')
display_event_count += 1
if display_event_count == display_events:
break
display_event_count = 0
for event in ds:
event_time = event['date']
event_playerid = player_id[event['actor']]
event_filename = f"2018-03-02_P{event_playerid}"
event_framenumber = utils.event_time_to_stream_frame(
event_time, event_playerid, 1)
video_path = f'C:\save\\{event_filename}.mp4'
vid = read_video(video_path)
event_type = event['event_type']
event_actor = event['actor']
display_video(vid,
event_framenumber - show_frames_before,
title=f'{event_type} {event_actor}')
display_event_count += 1
if display_event_count == display_events:
break
if __name__ == '__main__':
myDl = read_JSON.DataHandler()
myEventWindows = myDl.eventWindowArrayPerActor
"""for actor in myDl.actors:
print(actor)
for i in range(0, len(myDl.eventWindowArrayPerActor[actor])):
if myDl.eventWindowArrayPerActor[actor][i]["total_weight"] > 0:
print(myDl.eventWindowArrayPerActor[actor][i])"""